A customer would like to buy a given set of products in a given set of Internet shops. For each Internet shop, standard prices for the products are known as well as a concave increasing discounting function of total standard and delivery price. The problem is to buy all the required products at the minimum total discounted price. Computational complexity of various special cases is established. Properties of optimal solutions are proved and polynomial time and exponential time solution algorithms based on these properties are designed. Two heuristic algorithms are suggested and computationally tested.

A high number of Internet shops makes it difficult for a customer to review manually all the available offers and select optimal outlets for shopping. A partial solution to the problem is brought by price comparators which produce price rankings from collected offers. However, their possibilities are limited to a comparison of offers for a single product requested by the customer. The issue we investigate in this paper is a multiple-item multiple-shop optimization problem, in which total expenses of a customer to buy a given set of items should be minimized over all available offers. In this paper, the Internet Shopping Optimization Problem (ISOP) is defined in a formal way and a proof of its strong NP-hardness is provided. We also describe polynomial time algorithms for special cases of the problem.

This invited article looks at the practical and legal implications of cloud brokering, in which cloud service brokers act as intermediaries between cloud service providers and customers.he International Organization for Standardization defi nes a cloud service broker (CSB) as a "cloud service partner that negotiates relationships between cloud service customers and cloud service providers." 1 A cloud service partner is further explained as a "party which is engaged in support of, or auxiliary to, activities of either the cloud service provider or the cloud service customer or both." The second type of partner described in the standard is the cloud auditor. In other words, cloud brokering encompasses a wide range of activities. Essentially, it includes all intermediaries that stand between a cloud service provider (CSP) and a cloud service customer (CSC). The negotiation of relationships is most often understood as a proposition of contract that's satisfying for both customers and providers. Sustainable broker business models must create added value to ensure that CSCs have real interest in using broker services.Motivations for using broker services vary. First, using these services might be more advantageous from an economical viewpoint: CSBs might offer better conditions to customers than CSPs. On the other hand, CSBs might create new channel and marketing opportunities for CSPs, resulting in a growth of sales.A CSB might also take care of additional customer demands. For example, the data sent to the cloud might be subject to special security or compliancy regulations, such as specifi c requirements for data location, encryption, or format. A CSB could select services that fulfi ll these demands. It might also select offers compatible with the other products and services currently used by the consumer, minimizing the time and costs of transitioning to a new cloud. The CSB's selection could also be motivated by additional aspects, including the trust, reputation, environment-awareness (for example, use of green energy), or social responsibility of CSPs.

The rapid adoption of Internet of Things (IoT) has encouraged the integration of new connected devices such as Unmanned Aerial Vehicles (UAVs) to the ubiquitous network. UAVs promise a pragmatic solution to the limitations of existing terrestrial IoT infrastructure as well as bring new means of delivering IoT services through a wide range of applications. Owning to their potential, UAVs are expected to soon dominate the low-altitude airspace over populated cities. This introduces new research challenges such as the safe management of UAVs operation under high traffic demands. This paper proposes a novel way of structuring the uncontrolled, low-altitude airspace, with the aim of addressing the complex problem of UAV traffic management at an abstract level. The work, hence, introduces a model of the airspace as a weighted multilayer network of nodes and airways and presents a set of experimental simulation results using three UAV traffic management heuristics.